组合分段-线性回归模型的参数辨识

S. Noskov
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引用次数: 0

摘要

研究课题:组合分段线性回归模型的参数估计问题。研究目的:应用线性布尔规划方法辨识其参数。研究方法和对象:研究对象是一套俄罗斯联邦发明活动的指标,方法是回归分析和数学规划。主要研究成果:提出了一种用最小模量法估计组合分段线性回归模型参数的方法,使该问题可以简化为线性布尔规划问题。建立了俄罗斯联邦发明活动的分段线性组合模型,可用于各种分析和预测计算。模型的输出变量是专利申请量,输入变量是国内生产总值、研究生人数和教师人数。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Identification of parameters of a combined piece-linear regression model
Subject of research: the problem of estimating the parameters of a combined piecewise linear regression model. Purpose of research: to apply the apparatus of linear Boolean programming to identify its parameters. Methods and objects of research: the object of research is a set of indicators of inventive activity in the Russian Federation, the methods are regression analysis and mathematical programming. Main results of research: an approach to estimating the parameters of a combined piecewise linear regression model by using the method of least modules is described, which makes it possible to reduce this problem to a linear Boolean programming problem. A combined piecewise linear model of inventive activity in the Russian Federation has been constructed, which can be used in various analytical and predictive calculations. The output variable of the model is the number of patent applications, and the input variable is the volume of gross domestic product, the number of graduate students and teaching staff.
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